Vaughn College of Aeronautics and Technology

About: Vaughn College of Aeronautics and Technology is a education organization based out in New York, New York, United States. It is known for research contribution in the topics: Gravitational microlensing & Planetary system. The organization has 727 authors who have published 708 publications receiving 14082 citations. The organization is also known as: College of Aeronautics.

Rate rules for hydrogen abstraction reaction kinetics of polycyclic aromatic hydrocarbons and vinyl radical

Abstract: Hydrogen abstraction reaction from polycyclic aromatic hydrocarbons (PAHs) is an important reaction class for PAHs consumption and soot formation. In this work, the reaction kinetics for a series of PAHs containing up to seven aromatic rings by vinyl radical are systematically investigated using the M06-2X/cc-pVTZ method. Based on the electronic structure calculations, the rate constants of title reactions are calculated by using transition state theory coupled with Eckart tunneling correction at the temperature range of 500–2500 K. The effects of PAH sizes, structures, and reaction sites on the rate constants are examined. The results show that the PAH sizes and reaction sites have little effect on the rate constants, while the structures of PAHs influence the rate constant significantly. Hence, the hydrogen abstraction reactions are simplified into C5 and C6 reaction classes depending on the abstraction site on the five- or six-membered ring. The simple two classes are conducive to construct the combustion model of PAHs. The reactivity with C6 class possesses the higher activity than the C5 class. Moreover, the difference in rate constants between the two classes is large at low temperatures while the two reaction classes are competitive above 1000 K. The rate rules are summarized by taking the average values of rate constants of a representative set of reactions in each class, which are applicable for the chemical model construction of PAHs.

Repairing Human Trust by Promptly Correcting Robot Mistakes with An Attention Transfer Model

Abstract: In human-robot collaboration (HRC), human trust in the robot is the human expectation that a robot executes tasks with desired performance. A higher-level trust increases the willingness of a human operator to assign tasks, share plans, and reduce the interruption during robot executions, thereby facilitating human-robot integration both physically and mentally. However, due to real-world disturbances, robots inevitably make mistakes, decreasing human trust and further influencing collaboration. Trust is fragile and trust loss is triggered easily when robots show incapability of task executions, making the trust maintenance challenging. To maintain human trust, in this research, a trust repair framework is developed based on a human-to-robot attention transfer (H2R-AT) model and a user trust study. The rationale of this framework is that a prompt mistake correction restores human trust. With H2R-AT, a robot localizes human verbal concerns and makes prompt mistake corrections to avoid task failures in an early stage and to finally improve human trust. User trust study measures trust status before and after the behavior corrections to quantify the trust loss. Robot experiments were designed to cover four typical mistakes, wrong action, wrong region, wrong pose, and wrong spatial relation, validated the accuracy of H2R-AT in robot behavior corrections; a user trust study with 252 participants was conducted, and the changes in trust levels before and after corrections were evaluated. The effectiveness of the human trust repairing was evaluated by the mistake correction accuracy and the trust improvement.